Publications

Real-E: A Foundation Benchmark for Advancing Robust and Generalizable Electricity Forecasting
Shao, C.; Färber, M.; Pütz, S.; Schäfer, B.; Wang, Y.; Käfer, T.; Huang, Z.; Zhu, Z.
2025. CIKM ’25: The 34th ACM International Conference on Information and Knowledge Management Seoul Republic of Korea November 10 - 14, 2025, 6523–6527, Association for Computing Machinery (ACM). doi:10.1145/3746252.3761637

Deep Learning Approaches for the Detection of Ramping Artifacts in Schedule Deviation Data in Belgium
von Hülsen, H.; Oberhofer, U.; Lauwers, O.; Verbruggen, G.; Pütz, S.; Hagenmeyer, V.; Schäfer, B.
2025. 2025 IEEE Kiel PowerTech, 29 June 2025 - 03 July 2025, 1–8, Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/PowerTech59965.2025.11180720

Probabilistic and Explainable Machine Learning for Tabular Power Grid Data
Nikoltchovska, A.; Pütz, S.; Li, X.; Hagenmeyer, V.; Schäfer, B.
2025. Proceedings of the 16th ACM International Conference on Future and Sustainable Energy Systems, Rotterdam, 17th-20th June 2025, 213–231, Association for Computing Machinery (ACM). doi:10.1145/3679240.3734623

Explainable time-series forecasting with sampling-free SHAP based on attention manipulation
Hertel, M.; Pütz, S.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2025. Helmholtz AI Conference: AI for Science (HAICON 2025), Karlsruhe, Germany, June 3–5, 2025

Analysing and Predicting Extreme Frequency Deviations: A Case Study in the Balearic Power Grid
Sharfeddine, Z.; Pütz, S.; Tamhane, V.; Hagenmeyer, V.; Schäfer, B.
2024. ACM SIGEnergy Energy Informatics Review, 4 (4), 155–162. doi:10.1145/3717413.3717427

Feasibility of Forecasting Highly Resolved Power Grid Frequency Utilizing Temporal Fusion Transformers
Pütz, S.; El Ashhab, H.; Hertel, M.; Mikut, R.; Götz, M.; Hagenmeyer, V.; Schäfer, B.
2024. e-Energy ’24: Proceedings of the 15th ACM International Conference on Future and Sustainable Energy Systems, 447–453, Association for Computing Machinery (ACM). doi:10.1145/3632775.3661963

Identifying drivers and mitigators for congestion and redispatch in the German electric power system with explainable AI
Titz, M.; Pütz, S.; Witthaut, D.
2024. Applied Energy, 356, 122351. doi:10.1016/j.apenergy.2023.122351

AI serving grid stability: detecting anomalies in automatic frequency restoration data
Beichter, M.; Hertel, M.; Hülsen, H. von; Oberhofer, U.; Pütz, S.
2024, February 14. Hessian.AI Industry Challenge Final Event (2024), Online, February 13–14, 2024

Analysing and Predicting Extreme Frequency Deviations: A Case Study in the Balearic Power Grid
Sharfeddine, Z.; Pütz, S.; Tamhane, V.; Hagenmeyer, V.; Schäfer, B.
2024. Energy Informatics Review Newsletter: EIR Newsletter

Explainability and Benchmarking of Transformers for Time-Series Forecasting
Hertel, M.; Pütz, S.; Schäfer, B.; Mikut, R.; Hagenmeyer, V.
2024. Helmholtz Artificial Intelligence Conference (Helmholtz AI 2024), Düsseldorf, Germany, June 12–14, 2024

Probabilistic Forecasting of Day-Ahead Electricity Prices and their Volatility with LSTMs
Trebbien, J.; Pütz, S.; Schäfer, B.; Nygård, H. S.; Gorjão, L. R.; Witthaut, D.
2023. Powering solutions for decarbonized and resilient future smartgrids, 5 S., Institute of Electrical and Electronics Engineers (IEEE). doi:10.1109/ISGTEUROPE56780.2023.10407112

Forecasting Power Grid Frequency Trajectories with Structured State Space Models
Pütz, S.; Schäfer, B.
2023, June 28. 14th ACM International Conference on Future Energy Systems (e-Energy 2023), Orlando, FL, USA, June 20–23, 2023. doi:10.1145/3599733.3606298

Regulatory Changes in German and Austrian Power Systems Explored with Explainable Artificial Intelligence
Pütz, S.; Kruse, J.; Witthaut, D.; Hagenmeyer, V.; Schäfer, B.
2023. Companion Proceedings of the 14th ACM International Conference on Future Energy Systems (e-Energy ’23), 26–31, Association for Computing Machinery (ACM). doi:10.1145/3599733.3600247

Identifying drivers and mitigators for congestion and redispatch in the German electric power system with explainable AI
Titz, M.; Pütz, S.; Witthaut, D.
2023. doi:10.48550/arXiv.2307.12636